When deciding on wind power investments, three major issues arise: the production variability and uncertainty of wind facilities, the eventual future decline in wind power investment costs, and the significant financial risk involved in such investment decisions. Recognizing the above important issues, this presentation proposes a risk-constrained multi-stage stochastic programming model to make optimal investment decisions on wind power facilities along a multi-stage horizon. The proposed model is illustrated using a clarifying example and a case study.

Speaker Bio

Antonio J. Conejo, professor at The Ohio State University, OH, US, received the M.S. from MIT and the Ph.D. from the Royal Institute of Technology, Sweden. He has published over 150 papers in SCI journals and is the author or coauthor of books published by Springer, John Wiley, McGraw-Hill and CRC. He has been the principal investigator of many research projects financed by public agencies and the power industry and has supervised 18 PhD theses. He is the Editor-in-Chief of the IEEE Transactions on Power Systems and an IEEE Fellow.